Abstract
With the informatization of industrial control system, industrial communication protocol is facing greater data pressure. At the same time, industrial communication protocols will face more security threats. In this paper, we use the method of transforming STM (State Transition Matrix) model to UPPAAL (a tool for verifying real-time system) model. In order to clearly understand the model and avoid some mistakes in the early stage of modeling, we first establish STM model for Modbus TCP/IP protocol. Finally, it is transformed into UPPAAL model. Five types of attributes are verified by UPPAAL tool, including the verification of unreachable attributes found by STM modeling. These five types of attributes verify the credibility of Modbus TCP/IP protocol. The experimental results show that this method can have a clear understanding of the model in the early stage. After converting STM model into UPPAAL model, more constraints can be found by referring to STM model. Compared with the existing methods, it studies the credibility of the protocol itself. Therefore, the method can find the root of the problem and solve it.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Galloway, B., Hancke, G.P.: Introduction to industrial control networks. IEEE Commun. Surv. Tutor. 15(2), 860–880 (2012)
Schwartz, M., Mulder, J., Chavez, A.R., et al.: Emerging techniques for field device security. IEEE Secur. Priv. 12(6), 24–31 (2014)
Krotofil, M., Gollmann, D.: Industrial control systems security: what is happening? In: 2013 11th IEEE International Conference on Industrial Informatics (INDIN), pp. 670–675. IEEE (2013)
Mo, Y., Kim, T.H.J., Brancik, K., et al.: Cyber–physical security of a smart grid infrastructure. Proc. IEEE 100(1), 195–209 (2011)
Huang, S., Zhou, C.J., Yang, S.H., et al.: Cyber-physical system security for networked industrial processes. Int. J. Autom. Comput. 12(6), 567–578 (2015)
Wang, T., Lu, Y.C., Wang, J.H., et al.: EIHDP: edge-intelligent hierarchical dynamic pricing based on cloud-edge-client collaboration for IoT systems. IEEE Trans. Comput. 70(8), 1285–1298 (2021)
Wang, T., Liu, Y., Zheng, X., et al.: Edge-based communication optimization for distributed federated learning. IEEE Trans. Netw. Sci. Eng. (2021). https://doi.org/10.1109/TNSE.2021.3083263
Wu, Y.K., Huang, H.Y., Wu, N.Y., et al.: An incentive-based protection and recovery strategy for secure big data in social networks. Inf. Sci. 508, 79–91 (2020)
Stouffer, K., et al.: Guide to industrial control systems (ICS) security. NIST Spec. Publ. 800, 82 (2007)
Tsang, C., Kwong, S.: Multi-agent intrusion detection system in industrial network using ant colony clustering approach and unsupervised feature extraction. In: 2005 IEEE International Conference on Industrial Technology, pp. 51–56. IEEE (2005)
Gao, W., Morris, T., Reaves, B., Richey, D.: On SCADA control system command and response injection and intrusion detection. In: 2010 eCrime Researchers Summit, pp. 1–9. IEEE (2010)
Yusheng, W., et al.: IEEE 13th international symposium on autonomous decentralized system (ISADS). IEEE 2017, 156–162 (2017)
Tafto Rodfoss, J.: Comparison of open source network intrusion detection systems (2011)
Xu, Y., Yang, Y., Li, T., Ju, J., Wang, Q.: Review on cyber vulnerabilities of communication protocols in industrial control systems. In: 2017 IEEE Conference on Energy Internet and Energy System Integration (EI2), pp. 1–6. IEEE (2017)
Khummanee, S., Khumseela, A., Puangpronpitag, S.: Towards a new design of firewall: anomaly elimination and fast verifying of firewall rules. In: The 2013 10th International Joint Conference on Computer Science and Software Engineering (JCSSE), pp. 93–98. IEEE (2013)
Cheminod, M., Durante, L., Seno, L., Valenzano, A.: Performance evaluation and modeling of an industrial application-layer firewall. IEEE Trans. Industr. Inf. 14(5), 2159–2170 (2018)
Zhao, H., Li, Z., Wei, H., et al.: SeqFuzzer: an industrial protocol fuzzing framework from a deep learning perspective. In: 2019 12th IEEE Conference on Software Testing, Validation and Verification (ICST), pp. 59–67. IEEE (2019)
White, R., Caiazza, G., Jiang, C., et al.: Network reconnaissance and vulnerability excavation of secure DDS systems. In: 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW), pp. 57–66. IEEE (2019)
Behrmann, G., David, A., Larsen, K.G.: A tutorial on Uppaal. In: Bernardo, M., Corradini, F. (eds.) Formal Methods for the Design of Real-Time Systems, pp. 200–236. Springer, Heidelberg (2004). https://doi.org/10.1007/978-3-540-30080-9_7
Christian, N., Libero, N., Paolo, F.: Sciammarella: modelling and analysis of multi-agent systems using UPPAAL SMC. Int. J. Simulat. Process Model. 13(1), 73–87 (2018)
K, Eun-Young., D, M., H, L.: Probabilistic verification of timing constraints in automotive systems using UPPAAL-SMC. In: Furia, Carlo A., Winter, Kirsten (eds.) Integrated Formal Methods: 14th International Conference, IFM 2018, Maynooth, Ireland, September 5-7, 2018, Proceedings, pp. 236–254. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-98938-9_14
Lin, C., Yang, Z., Dai, H., Cui, L., Wang, L., Wu, G.: Minimizing charging delay for directional charging. IEEE/ACM Trans. Netw. 29(6), 2478–2493 (2021). https://doi.org/10.1109/TNET.2021.3095280
Lin, C., Zhou, J.Z., Guo, C.Y., et al.: TSCA: a temporal-spatial real-time charging scheduling algorithm for on-demand architecture in wireless rechargeable sensor networks. IEEE Trans. Mob. Comput. 17(1), 211–224 (2018)
Lin, C., Wang, Z.Y., Deng, J., et al.: mTS: Temporal- and Spatial-Collaborative Charging for Wireless Rechargeable Sensor Networks with Multiple Vehicles, pp. 99–107. IEEE (2018)
Lin, C., Shang, Z., Du, W., et al.: CoDoC: A Novel Attack for Wireless Rechargeable Sensor Networks through Denial of Charge, pp. 856–864. IEEE (2019)
Lin, C., Zhou, Y., Ma, F., et al.: Minimizing charging delay for directional charging in wireless rechargeable sensor networks. In: IEEE INFOCOM 2019-IEEE Conference on Computer Communications, pp. 1819–1827. IEEE (2019)
Modbus, I.: Modbus application protocol specification v1. 1a. North Grafton, Massachusetts (www. modbus. org/specs. php) (2004)
Matsumoto, M.: Model checking of state transition matrix. 2nd ITSSV, 2005, pp. 2–11 (2005)
Shiraishi, T., Kong, W., Mizushima, Y., et al.: Model checking of software design in state transition matrix. In: SERP 2010: Proceedings of the 2010 International Conference on Software Engineering Research & Practice, Las Vegas, 12–15 July 2010, pp. 507–513 (2010)
Acknowledgments
National Key Research and Development Project (Key Technologies and Applications of Security and Trusted Industrial Control System NO. 2020YFB2009500).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 Springer Nature Switzerland AG
About this paper
Cite this paper
Wang, J. et al. (2022). A Modeling and Verification Method of Modbus TCP/IP Protocol. In: Lai, Y., Wang, T., Jiang, M., Xu, G., Liang, W., Castiglione, A. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2021. Lecture Notes in Computer Science(), vol 13157. Springer, Cham. https://doi.org/10.1007/978-3-030-95391-1_33
Download citation
DOI: https://doi.org/10.1007/978-3-030-95391-1_33
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-95390-4
Online ISBN: 978-3-030-95391-1
eBook Packages: Computer ScienceComputer Science (R0)